Two-way sync
Changes in Apache Druid or Redis Enterprise instantly reflect in both systems. No stale data, no manual imports.
Keep Apache Druid and Redis Enterprise in sync without custom scripts. Cut weeks of integration work, eliminate silent data drift, and give your team a single, reliable source of truth.
Operational databases and analytical warehouses want the same data at different moments. Analysts want Redis Enterprise's rows in Apache Druid, current and joinable, without a change-data-capture pipeline to maintain. Engineers want the outputs of warehouse work, such as aggregates, features, and segments, available in Redis Enterprise where the services that read from it get them at normal query latency.
Stacksync covers both directions with one connection. Tables or collections in Redis Enterprise sync into Apache Druid in real time, and result tables in Apache Druid sync back into Redis Enterprise, with schema and type mapping between the two systems handled for you.
Point analytical queries at the synced copy in Apache Druid and keep Redis Enterprise focused on its operational workload.
Rows from Redis Enterprise land in Apache Druid as they change, replacing hand-built CDC and batch extract jobs.
Aggregates or model outputs computed in Apache Druid sync into Redis Enterprise, where whatever reads from that database gets them without querying the warehouse.
Representative objects on each side — any object or custom field can map to any target. Schemas are auto-detected; types are converted between the two systems.
| Apache Druid objects | Redis Enterprise objects | |
|---|---|---|
| Tasks Batch ingestion and compaction jobs monitored during data loads. | Keys (Strings) Simple key-value pairs used to cache individual synced records or lookup values. | |
| Datasources The table-like unit of storage and querying, the main target of reads and ingestion. | Hashes Field-value maps that commonly hold one synced row per hash, keyed by record ID. | |
| Segments Time-partitioned immutable files that hold datasource data; ingestion produces them. | JSON documents Native JSON storage (RedisJSON) for nested records synced from APIs or document stores. | |
| Dimensions String and categorical columns used for filtering and grouping in synced queries. | Sets Unordered unique-member collections used for membership checks like segment or ID lists. | |
| Metrics Numeric columns, often pre-aggregated at ingestion via rollup. | Sorted Sets Score-ordered collections used for rankings, priority queues, and time-ordered indexes. | |
| Ingestion Supervisors Long-running specs that pull from streams like Kafka; the write path into Druid. | Lists Ordered sequences often used as lightweight queues fed by sync events. |
Real-time sync, workflow automation, event queues, EDI, and monitoring, for every Apache Druid–Redis Enterprise connection.
Changes in Apache Druid or Redis Enterprise instantly reflect in both systems. No stale data, no manual imports.
Trigger automated workflows whenever Apache Druid or Redis Enterprise data changes, update records, fire webhooks, or kick off sequences without brittle API scripts.
Handle millions of events per minute without losing a single Apache Druid or Redis Enterprise record.
Track your Apache Druid ⇄ Redis Enterprise sync health, view errors, and replay failed events in one click.
Transform legacy EDI complexity into simple database interactions between Apache Druid and Redis Enterprise.
Configure and sync within minutes, no code. Whether you sync 50k or 100M+ records, Stacksync handles the queues, infra, and plumbing. Integrations are non-invasive and need zero setup on your systems.
Authenticate Apache Druid and Redis Enterprise with each platform's native method — OAuth, API keys, or service accounts — plus secure options like SSH tunneling, IP whitelisting, and VPC peering.
Pick the Apache Druid and Redis Enterprise objects to sync — Stacksync auto-detects both schemas, including custom fields where the platform exposes them. Sync to existing tables, or let Stacksync create new ones with ideal data types.
Fields map automatically even when names and types differ. Stacksync handles transformation and type casting for you, zero configuration required.
Yes. Stacksync provides a managed, real-time two-way integration between Apache Druid and Redis Enterprise: authenticate both systems, choose the objects to sync (such as Apache Druid's Tasks and Datasources), map fields visually, and changes propagate both ways in milliseconds — no code required.
Common patterns for Apache Druid and Redis Enterprise: Offload heavy reads; Operational data in the warehouse, minus the pipeline; Serve warehouse results at database speed. Point analytical queries at the synced copy in Apache Druid and keep Redis Enterprise focused on its operational workload.
Apache Druid: REST API (SQL over HTTP and native JSON queries); JDBC via Avatica. Authentication: Deployment-dependent: basic authentication or an authenticator extension; often fronted by a proxy. Redis Enterprise: Redis wire protocol (RESP) via client libraries; separate REST API for cluster management. Authentication: Password or ACL-based credentials, typically over TLS. Stacksync manages authentication, retries, and rate limits on both sides.
Apache Druid: Rollup can pre-aggregate events at ingestion time, meaning the stored granularity may differ from the raw event stream. Redis Enterprise: Keyspace notifications are delivered over pub/sub with no replay, so reliable change capture usually pairs them with Streams or periodic reconciliation. Stacksync's field mapping accounts for these differences between Apache Druid and Redis Enterprise without custom code.
Stacksync is SOC 2 Type II and ISO 27001 certified with HIPAA BAA support. Data is encrypted in transit, and a zero-persistent-storage architecture means Apache Druid and Redis Enterprise records are not retained after a sync operation.
Stacksync pricing is usage-based and starts at $1,000/month, including the managed Apache Druid and Redis Enterprise connectors, real-time two-way sync, monitoring, and support. That replaces building and maintaining a custom Apache Druid–Redis Enterprise integration in-house.
As a data company, we understand the importance of keeping your data secure. Stacksync is built with security best practices to keep your data safe at every layer, and is DPF-certified for US, EU, UK and CH data transfers.
Let your users access Stacksync from your centralized user management systems. Works with Okta, Azure, Google SSO and more.
Immediately get alerted about record syncing issues over email, Slack, PagerDuty and WhatsApp. Resolve issues from a centralized dashboard with retry and revert options.
Securely connects to your systems with:
Every pair below is a real-time, two-way sync. Search all 386 integrations available for Apache Druid and Redis Enterprise.